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Network Security Situation Prediction Based on TCAN-BiGRU Optimized by SSA and IQPSO 被引量:1
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作者 Junfeng Sun Chenghai Li +2 位作者 Yafei Song Peng Ni Jian Wang 《Computer Systems Science & Engineering》 SCIE EI 2023年第10期993-1021,共29页
The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To ... The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To solve these problems,a combined prediction model based on the temporal convolution attention network(TCAN)and bi-directional gate recurrent unit(BiGRU)network is proposed,which is optimized by singular spectrum analysis(SSA)and improved quantum particle swarmoptimization algorithm(IQPSO).This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data.Furthermore,a prediction model of TCAN-BiGRU is established respectively for each subsequence.TCAN uses the TCN to extract features from the network security situation data and the improved channel attention mechanism(CAM)to extract important feature information from TCN.BiGRU learns the before-after status of situation data to extract more feature information from sequences for prediction.Besides,IQPSO is proposed to optimize the hyperparameters of BiGRU.Finally,the prediction results of the subsequence are superimposed to obtain the final predicted value.On the one hand,IQPSO compares with other optimization algorithms in the experiment,whose performance can find the optimum value of the benchmark function many times,showing that IQPSO performs better.On the other hand,the established prediction model compares with the traditional prediction methods through the simulation experiment,whose coefficient of determination is up to 0.999 on both sets,indicating that the combined prediction model established has higher prediction accuracy. 展开更多
关键词 Network security situation prediction SSA IQPSO TCAN-BiGRU
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Network Security Situation Prediction Based on Improved Adaptive Grey Verhulst Model 被引量:4
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作者 胡威 李建华 +1 位作者 陈秀真 蒋兴浩 《Journal of Shanghai Jiaotong university(Science)》 EI 2010年第4期408-413,共6页
Network security situation is a hot research topic in the field of network security. Whole situation awareness includes the current situation evaluation and the future situation prediction. However, the now-existing r... Network security situation is a hot research topic in the field of network security. Whole situation awareness includes the current situation evaluation and the future situation prediction. However, the now-existing research focuses on the current situation evaluation, and seldom discusses the future prediction. Based on the historical research, an improved grey Verhulst model is put forward to predict the future situation. Aiming at the shortages in the prediction based on traditional Verhulst model, the adaptive grey parameters and equal- dimensions grey filling methods are proposed to improve the precision. The simulation results prove that the scheme is efficient and applicable. 展开更多
关键词 network security situation situation prediction grey theory grey Verhulst model
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A Modularity Analysis Method for Forum Situation Prediction 被引量:1
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作者 QIAN Ailing QU Binbin +1 位作者 LU Yansheng HUANG Jin 《Wuhan University Journal of Natural Sciences》 CAS 2011年第2期148-154,共7页
A forum is a social network that consists of posters and the following comments made by netizens. Generally speaking, forum topics are evolving over time dynamically. In this paper, based on time series analysis and m... A forum is a social network that consists of posters and the following comments made by netizens. Generally speaking, forum topics are evolving over time dynamically. In this paper, based on time series analysis and matrix modularity analysis, a novel prediction method is proposed through investigating the correlating influence of three key measurements: relationship strength, pillars, and change frequency of a forum topic. The method demonstrates that there exist some macroscopic and potential laws for forum situation prediction. Extensive experiments over large many datasets show the efficiency and effectiveness of the algorithms. 展开更多
关键词 time series social network forum sentiment situation prediction modularity analysis
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System Architecture and Key Technologies of Network Security Situation Awareness System YHSAS 被引量:7
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作者 Weihong Han Zhihong Tian +2 位作者 Zizhong Huang Lin Zhong Yan Jia 《Computers, Materials & Continua》 SCIE EI 2019年第4期167-180,共14页
Network Security Situation Awareness System YHSAS acquires,understands and displays the security factors which cause changes of network situation,and predicts the future development trend of these security factors.YHS... Network Security Situation Awareness System YHSAS acquires,understands and displays the security factors which cause changes of network situation,and predicts the future development trend of these security factors.YHSAS is developed for national backbone network,large network operators,large enterprises and other large-scale network.This paper describes its architecture and key technologies:Network Security Oriented Total Factor Information Collection and High-Dimensional Vector Space Analysis,Knowledge Representation and Management of Super Large-Scale Network Security,Multi-Level,Multi-Granularity and Multi-Dimensional Network Security Index Construction Method,Multi-Mode and Multi-Granularity Network Security Situation Prediction Technology,and so on.The performance tests show that YHSAS has high real-time performance and accuracy in security situation analysis and trend prediction.The system meets the demands of analysis and prediction for large-scale network security situation. 展开更多
关键词 Network security situation awareness network security situation analysis and prediction network security index association analysis multi-dimensional analysis
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Remaining Useful Life Prediction for Aero-Engines Combining Sate Space Model and KF Algorithm 被引量:3
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作者 Cai Jing Zhang Li Dong Ping 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2017年第3期265-271,共7页
The key to failure prevention for aero-engine lies in performance prediction and the exhaust gas temperature margin(EGTM)is used as the most important degradation parameter to obtain the operating performance of the a... The key to failure prevention for aero-engine lies in performance prediction and the exhaust gas temperature margin(EGTM)is used as the most important degradation parameter to obtain the operating performance of the aero-engine.Because of the complex environment interference,EGTM always has strong randomness,and the state space based degradation model can identify the noisy observation from the true degradation state,which is more close to the actual situations.Therefore,a state space model based on EGTM is established to describe the degradation path and predict the remaining useful life(RUL).As one of the most effective methods for both linear state estimation and parameter estimation,Kalman filter(KF)is applied.Firstly,with EGTM degradation data,state space model approach is used to set up a state space model for aero-engine.Secondly,RUL of aero-engine is analyzed,and expected RUL and distribution of RUL are determined.Finally,the sate space model and KF algorithm are applied to an example of CFM-56aero-engine.The expected RUL is predicted,and corresponding probability density distribution(PDF)and cumulative distribution function(CDF)are given.The result indicates that the accuracy of RUL prediction reaches 7.76%ahead 580 flight cycles(FC),which is more accurate than linear regression,and therefore shows the validity and rationality of the proposed method. 展开更多
关键词 prediction remaining noisy situations exhaust ahead rationality validity cumulative Bayesian
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Predicted Employment Situation from 1996 to 2000
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《China Population Today》 1996年第3期7-7,共1页
PredictedEmploymentSituationfrom1996to2000¥//TheSocialDevelopmentDepartmentoftheStatePlanningCommissioninits... PredictedEmploymentSituationfrom1996to2000¥//TheSocialDevelopmentDepartmentoftheStatePlanningCommissioninitsreport,"AnAnalysi... 展开更多
关键词 Predicted Employment situation from 1996 to 2000
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WNN-Based Network Security Situation Quantitative Prediction Method and Its Optimization 被引量:4
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作者 赖积保 王慧强 +3 位作者 刘效武 梁颖 郑瑞娟 赵国生 《Journal of Computer Science & Technology》 SCIE EI CSCD 2008年第2期222-230,共9页
The accurate and real-time prediction of network security situation is the premise and basis of preventing intrusions and attacks in a large-scale network. In order to predict the security situation more accurately, a... The accurate and real-time prediction of network security situation is the premise and basis of preventing intrusions and attacks in a large-scale network. In order to predict the security situation more accurately, a quantitative prediction method of network security situation based on Wavelet Neural Network with Genetic Algorithm (GAWNN) is proposed. After analyzing the past and the current network security situation in detail, we build a network security situation prediction model based on wavelet neural network that is optimized by the improved genetic algorithm and then adopt GAWNN to predict the non-linear time series of network security situation. Simulation experiments prove that the proposed method has advantages over Wavelet Neural Network (WNN) method and Back Propagation Neural Network (BPNN) method with the same architecture in convergence speed, functional approximation and prediction accuracy. What is more, system security tendency and laws by which security analyzers and administrators can adjust security policies in near real-time are revealed from the prediction results as early as possible. 展开更多
关键词 network security situation prediction genetic algorithm wavelet analysis neural network
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